Genome-wide association mapping of transcriptome variation in Mimulus guttatus indicates differing patterns of selection on cis- versus trans-acting mutations

• Published in: Genetics (Austin) 2022-01, Vol.220 (1)
• Main Authors: Brown, Keely E, Kelly, John K
• Format: Article
• Language: English
• Subjects: Alleles; Flowers - genetics; Frequency spectrum; Gene expression; Gene Expression Regulation, Plant; Gene Frequency; Gene mapping; Genes; Genetic effects; Genetics; Genome, Plant; Genome-Wide Association Study - methods; Genomes; Intermediate frequencies; Investigation; Mimulus - genetics; Mimulus guttatus; Modules; Mutation; Nucleotides; Polymorphism, Single Nucleotide; Selection, Genetic; Single-nucleotide polymorphism; Skewed distributions; Transcription; Transcriptome; Transcriptomes
• ISSN: 1943-2631; 0016-6731; 1943-2631
• DOI: 10.1093/genetics/iyab189

Abstract We measured the floral bud transcriptome of 151 fully sequenced lines of Mimulus guttatus from one natural population. Thousands of single nucleotide polymorphisms (SNPs) are implicated as transcription regulators, but there is a striking difference in the allele frequency spectrum of cis-acting and trans-acting mutations. Cis-SNPs have intermediate frequencies (consistent with balancing selection) while trans-SNPs exhibit a rare-alleles model (consistent with purifying selection). This pattern only becomes clear when transcript variation is normalized on a gene-to-gene basis. If a global normalization is applied, as is typically in RNAseq experiments, asymmetric transcript distributions combined with “rarity disequilibrium” produce a superabundance of false positives for trans-acting SNPs. To explore the cause of purifying selection on trans-acting mutations, we identified gene expression modules as sets of coexpressed genes. The extent to which trans-acting mutations influence modules is a strong predictor of allele frequency. Mutations altering expression of genes with high “connectedness” (those that are highly predictive of the representative module expression value) have the lowest allele frequency. The expression modules can also predict whole-plant traits such as flower size. We find that a substantial portion of the genetic (co)variance among traits can be described as an emergent property of genetic effects on expression modules. Brown and Kelly perform a genome-wide association study on the transcriptome of yellow monkeyflower using previously sequenced inbred lines. They find a striking difference in the minor allele frequency spectrum of SNPs affecting gene expression in cis vs. in trans. The authors show that gene co-expression modules can predict fitness-related life-history phenotypes that experience fitness tradeoffs in field studies.